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Software-defined networking (SDN) is reshaping the networking paradigm. Previous research shows that SDN has advantages over traditional networks because it separates the control and data plane, leading to greater flexibility through network automation and programmability. Small business networks require flexibility, like service provider networks, to scale, deploy, and self-heal network infrastructure that comprises of cloud operating systems, virtual machines, containers, vendor networking equipment, and virtual network functions (VNFs); however, as SDN evolves in industry, there has been limited research to develop an SDN architecture to fulfil the requirements of small business networks. This research proposes a network architecture that can abstract, orchestrate, and scale configurations based on small business network requirements. Our results show that the proposed architecture provides enhanced network management and operations when combined with the network orchestration application (NetO-App) developed in this research. The NetO-App orchestrates network policies, automates configuration changes, and manages internal and external communication between the campus networking infrastructure.While SDN can be difficult to define, the Open Networking Foundation (ONF) defines an SDN architecture as a networking model that is directly and programmatically configured, decouples the network control functions from the forwarding functions, logically centralizes the control, and is open standards-based and vendor-neutral [3]. In a small business networking environment, the infrastructure incorporates both SDN and traditional devices and must use an architecture that can flexibly manage both traditional and SDN domains [13].Traditional network engineering relies on device configuration via the command line interface (CLI) and does not scale to meet the complexity of multi-vendor SDN/traditional networks in small businesses. Programmability of traditional devices is cumbersome because they lack open, programmable interfaces, which prohibits developers from programming the network in the most efficient method [21,22]. Furthermore, integrating SDN and traditional networks is difficult due to the disparities between how they function: traditional networks operate with the help of MAC address tables and routing tables, whereas SDN with OpenFlow uses flow entries in flow tables. These disparities need a different methodology to integrate as a system, and research indicates that only a limited number of tools can handle these problems efficiently [23].Network automation reduces the manual effort required for completing routine tasks and decreases the amount of human error caused by traditional, manual CLI configurations. Starting with scripting and progressing to intelligent network control and efficient translation and deployment of network plans and policies, network automation is a key tool to facilitate traditional network management and operations. While using information from configuration files and deploying routin...

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Discrete, non-virtualized network elements are characterized by large costs, limited functions, vendor lock-in, and limited orchestration. Virtualization technologies like virtual machines (VM) and containers have expanded the scope of virtual resource utilization through consolidation of workloads that were previously running on multiple servers by running them on a single server. With the advent of Network Functions Virtualization (NFV), industries are able to reduce the micro-economic factors associated with vendor proprietary model such as transaction costs and (physical and human) asset specificity to deal with vendor vulnerabilities in contractual relationships because Virtual Network Functions (VNFs) can virtualize dedicated networking functions that were traditionally performed by vendor appliances such as routers, switches, firewalls, and load balancers. Even though virtualization technologies (VMs and containers) and NFV have demonstrated their benefits in the market, little attention has been devoted to the development and adoption of containers to build VNFs. This research paper identifies micro-economic factors, such as transaction costs, associated with searching, buying, provisioning, and maintenance of vendor proprietary appliances and compares them with the coordination costs associated with the adoption of containerized VNFs. This comparative analysis could be used to identify the type of network operators that could serve as key organizers (the network operator who can benefit largely by adopting containerized VNFs) of an open source peer production model as well as other firms that could serve as individual contributors. Furthermore, to identify various rewards and incentives that a managerial firm can leverage to motivate its employees to participate in such an effort, a quantitative survey was conducted (with Tier 1, Tier 2 and Tier 3 Service Providers) to identify the managerial incentives such as bonuses, rewards, peer recognition, and promotion targeting varied network operator firms to accurately capture and analyze employee interests/motivation.

Service Function Chaining (SFC) is a capability that links multiple network functions to deploy end-to-end network services. By virtualizing these network functions also known as Virtual Network Functions (VNFs), the dependency on traditional hardware can be removed, hence making it easier to deploy dynamic service chains over the cloud environment. Before implementing service chains over a large scale, it is necessary to understand the performance overhead created by each VNF owing to their varied characteristics. This research paper attempts to gain insights on the server and networking overhead encountered when a service chain is deployed on a cloud orchestration tool such as OpenStack. Specifically, this research will measure the CPU utilization, RAM usage and System Load of the server hosting OpenStack. Each VNF will be monitored for its varying performance parameters when subjected to different kinds of traffic. Our focus lies on acquiring performance parameters of the entire system for different service chains and compare throughput, latency, and VNF statistics of the virtual network. Insights obtained from this research can be used in the industry to achieve optimum performance of hardware and network resources while deploying service chains.